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Statistical Decision Theory and Related Topics IV
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Table of Contents

1 - Conditioning and Likelihood.- What Is the Likelihood Function?.- Discussion.- Discussion.- Reply to Discussion.- The Relevance of Stopping Rules in Statistical Inference.- Discussion.- Discussion.- Discussion.- Reply to Discussion.- Conditionally Acceptable Frequentist Solutions.- Discussion.- Discussion.- Discussion.- Discussion.- Discussion.- Reply to Discussion.- On the Validity of the Likelihood Principle.- Resampling Generated Likelihoods.- 2 - Bayes and Empirical Bayes Analysis.- Bayesian Linear Probabilistic Classification.- Bayesian Numerical Analysis.- Estimating Logistic Regression Probabilities.- Bayes and Empirical Bayes Analysis in Multistage Sampling.- Empirical Bayes Rules for Selecting the Best Binomial Population.- A Bayesian Treatment of Multivariate Normal Data with Observations Missing at Random.- Causality Assessment for Adverse Drug Reactions: An Application of Subjective Probability to Medical Decision Making.- Determining the Accuracy of Bayesian Empirical Bayes Estimates in the Familiar Exponential Families.- The U,V Method of Estimation.- Some Results on Robustness in Testing.- 3 - Decision-Theoretic Estimation.- Shrinkage Estimators: Pseudo-Bayes Rules for Normal Mean Vectors.- The Differential Inequality of a Statistical Estimation Problem.- Bayesian Estimation Subject to Minimaxity of the Mean of a Multivariate Normal Distribution in the Case of a Common Unknown Variance: A Case for Bayesian Robustness.- New Estimators for the Mean Vector of a Normal Distribution with Unknown Covariance Matrix.- On Inadmissibility of Some Unbiased Estimates of Loss.- Dominating Inadmissible Procedures Using Compromise Decision Theory.- On Estimating Characteristic Roots in a Two-Sample Problem.- On Admissible Estimation in Exponential Families with Imprecise Information.- Estimated Loss and Admissible Loss Estimators.

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